Advertisement

Stance and Credibility Based Trust in Social-Sensor Cloud Services

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11234)

Abstract

We propose a users’ stance and credibility based social-sensor cloud service trust model. We represent social media data streams, i.e., image meta-data and related posted information, as social-sensor cloud services. We use the textual features of the social-sensor cloud services, i.e., comments, and meta-data, e.g., spatio-temporal information, to gather the trust-rate of the services and the credibility of users’ comments. The analytical results present the performance of the proposed model.

Keywords

Social-sensor Social-sensor cloud service Trust in social-sensor cloud service 

Notes

Acknowledgement

This research was partly made possible by NPRP 9-224-1-049 grant from the Qatar National Research Fund (a member of The Qatar Foundation) and DP1501 00149 and LE180100158 grants from Australian Research Council. The statements made herein are solely the responsibility of the authors.

References

  1. 1.
    Rosi, A., Mamei, M., Zambonelli, et al.: Social sensors and pervasive services: approaches and perspectives. In: Proceedings of PERCOM (2011)Google Scholar
  2. 2.
    Aggarwal, C.C., Abdelzaher, T.: Social sensing. In: Aggarwal, C. (ed.) Managing and Mining Sensor Data, pp. 237–297. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-1-4614-6309-2_9CrossRefGoogle Scholar
  3. 3.
    Aamir, T., Bouguettaya, A., Dong, H., et al.: Social-sensor cloud service selection. In: Proceedings of IEEE ICWS, pp. 508–515 (2017)Google Scholar
  4. 4.
    Aamir, T., Bouguettaya, A., Dong, H., Mistry, S., Erradi, A.: Social-sensor cloud service for scene reconstruction. In: Proceedings of ICSOC, pp. 37–52 (2017)CrossRefGoogle Scholar
  5. 5.
    Popat, K., Kashyap, S., et al.: Where the truth lies: explaining the credibility of emerging claims on the web and social media. In: Proceedings of WWW, pp. 1003–1012 (2017)Google Scholar
  6. 6.
    Gupta, A., Lamba, H., Kumaraguru, P., Joshi, A.: Faking sandy: characterizing and identifying fake images on twitter during hurricane sandy. In: Proceedings of WWW, pp. 729–736 (2013)Google Scholar
  7. 7.
    Mendoza, M., Poblete, B., Castillo, C.: Twitter under crisis: can we trust what we RT?. In: Proceedings of the First Workshop on Social Media Analytics, pp. 71–79. ACM (2010)Google Scholar
  8. 8.
    Gupta, A., Kumaraguru, P., Castillo, C., Meier, P.: TweetCred: real-time credibility assessment of content on Twitter. In: Proceedings of SocInfo, pp. 228–243 (2014)Google Scholar
  9. 9.
    Aamir, T., Bouguettaya, A., Dong, H.: Trust in social-sensor cloud service. In: Proceedings of IEEE ICWS (2018)Google Scholar
  10. 10.
    Allcott, H., Gentzkow, M.: Social media and fake news in the 2016: election. J. Econ. Perspect. 31, 211–236 (2016)CrossRefGoogle Scholar
  11. 11.
    Schifferes, S., Newman, N., Thurman, N., Corney, D., Gker, A., Martin, C.: Identifying and verifying news through social media: developing a user-centered tool for professional journalists. Digit. Journalism 2, 406–418 (2014)CrossRefGoogle Scholar
  12. 12.
    Shu, K., Sliva, A., Wang, S., et al.: Fake news detection on social media: a data mining perspective. In: Proceedings of ACM SIGKDD, pp. 22–36 (2017)CrossRefGoogle Scholar
  13. 13.
    Du, W., Lin, H., Sun, J., et al.: A new trust model for online social networks. In: Proceedings of IEEE ICCCI, pp. 300–304 (2016)Google Scholar
  14. 14.
    Lin, D.: An information-theoretic definition of similarity. In: Proceedings of ICML, pp. 296–304 (1998)Google Scholar
  15. 15.
    Malik, Z., Bouguettaya, A.: RATEWeb: reputation assessment for trust establishment among web services. VLDB J. 18, 885–911 (2009)CrossRefGoogle Scholar
  16. 16.
    Malik, Z., Bouguettaya, A.: Rater credibility assessment in web services interactions. In: Proceedings of WWW, pp. 3–25 (2009)CrossRefGoogle Scholar
  17. 17.
    Liu, X., et al.: Ev-LCS: a system for the evolution of long-term composed services. IEEE Trans. Serv. Comput. 6(1), 102–115 (2013)CrossRefGoogle Scholar
  18. 18.
    Li, L., Liu, D., Bouguettaya, A.: Semantic based aspect-oriented programming for context-aware Web service composition. Inf. Syst. 36(3), 551–564 (2011)CrossRefGoogle Scholar
  19. 19.
    Aamir, T., Dong, H., Bouguettaya, A.: Social-sensor composition for scene analysis. In: Proceedings of ICSOC (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of ScienceRMIT UniversityMelbourneAustralia
  2. 2.School of Information TechnologiesThe University of SydneySydneyAustralia

Personalised recommendations